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Internship Bank Data Scientist Jobs in Rochester, NY

Digital Analyst Internships

Geneseo, NY

$95K - $112K/yr

By submitting your interest, you'll be among the first to know when internship opportunities open ... Computer Science, Information Systems, or a related field * Familiarity with data analysis ...

Digital Analyst Internships

Rochester, NY

$97K - $115K/yr

By submitting your interest, you'll be among the first to know when internship opportunities open ... Computer Science, Information Systems, or a related field * Familiarity with data analysis ...

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Showing results 1-20

Internship Bank Data Scientist information

See Rochester, NY salary details

$45.4K

$162.8K

$240.3K

How much do internship bank data scientist jobs pay per year?

As of Aug 8, 2026, the average yearly pay for internship bank data scientist in Rochester, NY is $162,818.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,700.00 and $167,700.00 per year, depending on experience, location, and employer.

What does an internship bank data scientist do?

An Internship Bank Data Scientist assists banking organizations in analyzing large sets of financial data to uncover trends, improve decision-making, and enhance services. Their work typically involves cleaning and preparing data, applying statistical models, and creating visualizations to communicate insights. Interns often collaborate with senior data scientists and other departments to support projects related to risk assessment, fraud detection, and customer analytics. This role provides hands-on experience with industry-standard tools and real-world banking data, offering valuable exposure to the field.

What types of projects does an internship bank data scientist typically work on, and how do these projects contribute to the bank's objectives?

Internship Bank Data Scientists often work on projects involving data analysis, predictive modeling, and process automation to support departments like risk management, marketing, and customer analytics. These projects might include developing models to detect fraudulent transactions, segmenting customers for targeted offers, or optimizing internal workflows. Interns collaborate closely with senior data scientists, analysts, and IT teams, gaining exposure to real-world banking datasets and tools. The work completed by interns not only contributes to the bank’s data-driven decision making but also provides valuable, hands-on experience that can lead to future full-time opportunities.

What are the key skills and qualifications needed to thrive as an internship bank data scientist, and why are they important?

To thrive as an Internship Bank Data Scientist, you need a solid understanding of statistics, data analysis, and programming languages like Python or R, often supported by coursework or a degree in data science, mathematics, or a related field. Familiarity with data visualization tools (e.g., Tableau), SQL databases, and machine learning libraries is typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help you interpret data and convey insights to non-technical stakeholders. These skills are crucial for transforming complex data into actionable strategies that support banking operations and decision-making.

What is the difference between Internship Bank Data Scientist vs Data Analyst?

AspectInternship Bank Data ScientistData Analyst
Required CredentialsTypically pursuing or holding a degree in Data Science, Statistics, or related fieldsOften holds a degree in Data Analysis, Statistics, or related fields
Work EnvironmentInternship setting within financial institutions or banks, focusing on data modeling and analysisVaries from finance to marketing, working with data visualization and reporting
Employer & Industry UsageUsed by banks and financial firms for data-driven decision making during internshipsCommon across industries for interpreting data and supporting business decisions

The Internship Bank Data Scientist role is an entry-level position focused on developing data science skills within banking environments, often as part of an internship program. In contrast, Data Analysts typically work across various industries, focusing on data interpretation and reporting. While both roles require analytical skills and familiarity with data tools, the Data Scientist role emphasizes modeling and machine learning, whereas Data Analysts focus more on data visualization and descriptive analysis.

What cities near Rochester, NY are hiring for Internship Bank Data Scientist jobs? Cities near Rochester, NY with the most Internship Bank Data Scientist job openings:

$113K - $135K/yr

Full-time

Re-posted 13 days ago


Job description

Position: Data Platform Engineer
Location: Rochester, NY
Duration: 12+ Months
Hadoop and Informatica experience are a MUST
Description:
The Data Platform Engineer engages in the design, development and maintenance of the big data platform. This platform hosts structured and non-structured data sets that support various business operations and enable data-driven decisions. The role involves administering various data-hub ecosystem open source software tools along with other vendor supported tools like HortonWorks Hadoop, CISCO DV, IBM COGNOS tools. The DPE will work closely with Data Scientists, infrastructure Administrators and Data Platform Architects to ensure the platform meets business demands.
Essential Resource Responsibilities / Accountabilities: Level I- Installs and /or upgrades, configures, administers and troubleshoots the data hub software environment in order to achieve a reliable, highly available, well performing system- Provides direct technical support to data warehouse user community, and triages support to appropriate personnel when technical support is not sufficient.- Develops standards, policies and procedures for the form, structure and attributes of the data warehouse tools and systems - Develops data/information quality metrics- Develops processes to monitor cluster performance and resource usage- Works with Server Engineers to install new nodes, resolve node failures, and apply patches and upgrades- Maintains processes that feed data from various systems across the enterprise, ensuring data quality and process efficiency- Follows and helps streamline procedures for provisioning access to the BI system and establishing security Minimum Resource Qualifications:- Bachelor's degree in Information Technology, Computer Science, Software Engineering, or closely related field (or four additional years related work experience in lieu of bachelors)- Related work experience (i.e. Co-ops/Internships) preferred- Ability to take initiative and have a strong vision for driving large scale distributed data platforms- Experience with ecosystem components such as Hadoop, Cisco DV, Cognos, etc- Familiarity with Linux system administration, Linux scripting and networking skills- Proficiency in a programming language such as Python or Java is a plus- Experience with relational and NoSQL databases, including modeling and writing complex queries is a plus- MUST have EXCELLENT communication and
analytical skills Level I - Ability to perform routine tool maintenance working with the vendors and others on the team- Ability to identify data warehouse application and data issues- Monitor system uptime and performance- Escalate appropriately to management and/or more senior Tool Administrators- Minimum of 3 years' experience in tool administration- Demonstrated experience with Data Warehousing- Proactively identify and address risks on system before they become systems issues- Research and resolve data warehouse application and data issues
Physical Requirements- Ability to travel across regions Physical Requirements: In support of the Americans with Disabilities Act, this resource requirements document lists only those responsibilities and qualifications deemed essential to the position Equal Opportunity
Employer: As such, requires all suppliers of temporary staffing resources to affirm the rights of every person to participate in all aspects of employment without regard to race, color, sex/gender, age, disability, religion, creed, citizenship status, national origin, veteran status, military status, marital status, familial status, domestic violence victim status, sexual orientation, gender identity, predisposing genetic characteristic, genetic information, or any other status protected under the law